Deformación superficial en la ciudad de Santo Domingo usando small baseline subset (SBAS)

José Ramón Martínez Batlle
Autonomous University
of Santo Domingo (UASD)


https://geofis.github.io/sd-sbas/

Motivation

CORS RDSD

Context

SRTM DEM

Geological map (Servicio Geológico Nacional, 2020)

InSAR and derivatives

“Image of an earthquake”, Massonnet et al., Nature (1993)

Co-seismic interferogram (wrapped phase, Sentinel 1), earthquake 29/Dec/2020 (M6.4) near Petrinja & Sisak, Croatia. Each fringe ~2.8cm of deformation in the satellite line-of-sight

Co-seismic interferogram (wrapped phase, Sentinel 1), earthquake occurred 23/Sept/2018 (M5.2), Villa Elisa, Dominican Republic. Each fringe (complete color cycle) represents ~ 2.8 cm of ground deformation in the satellite line-of-sight

Platforms-Missions. Elliott et al., Nat. Comm. (2016)

Interferogram

https://www.ga.gov.au/scientific-topics/positioning-navigation/geodesy/geodetic-techniques/interferometric-synthetic-aperture-radar

Materials and methods

Generic workflow

  1. Align the reference and repeat images to sub-pixel accuracy

  2. The second step is to multiply the two SLC images to form the complex interferogram

  3. Extract the phase of the interferogram

Phase of the interferogram (Sandwell, Mellors, Tong, Wei, & Wessel, 2011)

Contributions to phase (Sandwell et al., 2011)

Forming interferograms in GMTSAR

Workflow in GMTSAR, 2-pass processing (Sandwell et al., 2011)

SBAS

  • This technique uses a combination of DInSAR produced by data pairs on a small orbital separation (baseline) in order to limit the spatial decorrelation

  • Possibly, more than one independent acquisition subset will be generated; thus, the latter have to be ‘linked’ each others.

  • Independent SAR acquisition datasets, separated by large baselines, are linked by the application of the SVD method, increasing the observation temporal sampling rate

(Berardino, Fornaro, Lanari, & Sansosti, 2002; Casu, Manconi, Pepe, & Lanari, 2011)

Athmospheric delay example (Barahona)

Scenes

u-blox GNSS

  • TESTED with recent SBAS, not used for 2016-2018 time-series.

Parts list

Fecha Parte Precio
7/jul/2019 Raspberry Pi 3 B+ US$38
8/jul/2019 u-blox NEO-M8T US$75
16/jul/2019 Pantalla táctil Waveshare 480x320 US$33
17/ago/2019 Atenna TOPGNSS (sustituyó antena u-blox) US$53
18/ago/2019 Impresión 3D de caja, repo GitHub de Taroz US$37
17/ago/2019 2 Baterías 8800mAh NP-F970 (Sony) con cargador US$38
21/ago/2019 Adaptador para batería, conversor a ~5V, cables US$28
13/sep/2019 Trípode US$45
25/oct/2019 Palo 2 m con nivel de burbuja US$65
Total sin ensamblar US$161
Total ensamblada US$302
Total ensamblada con trípode US$347
Total ensamblada con trípode y palo US$412

Results

Validation of corrected time-series

References

Berardino, P., Fornaro, G., Lanari, R., & Sansosti, E. (2002). A new algorithm for surface deformation monitoring based on small baseline differential sar interferograms. IEEE Transactions on Geoscience and Remote Sensing, 40(11), 2375–2383.

Casu, F., Manconi, A., Pepe, A., & Lanari, R. (2011). Deformation time-series generation in areas characterized by large displacement dynamics: The sar amplitude pixel-offset sbas technique. IEEE Transactions on Geoscience and Remote Sensing, 49(7), 2752–2763.

Sandwell, D., Mellors, R., Tong, X., Wei, M., & Wessel, P. (2011). An insar processing system based on generic mapping tools. UC San Diego: Scripps Institution of Oceanography Technical Report.

Servicio Geológico Nacional. (2020). Mapa geológico de la república dominicana, escala 1:250,000. Retrieved December 31, 2020, from https://sgn.gob.do/images/docs/mapa_geologico.pdf